Lance Nelson

 Lance Nelson

Lance J. Nelson

  • Courses8
  • Reviews27
Dec 28, 2019
N/A
Textbook used: Yes
Would take again: Yes
For Credit: Yes

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Mandatory



Difficulty
Clarity
Helpfulness

Good

Professor Nelson's lectures are amazing. He's good at answering students' questions too. The workday system works perfectly, in my experience.

Biography

Brigham Young University Idaho - Physics

Physics Faculty at BYU-Idaho
Research
Lance
Nelson, Ph.D
Rexburg, Idaho
Highly motivated materials scientist seeking opportunities in computational materials research.


Experience

  • Brigham Young University

    Postdoctoral researcher

    Developed a kinetic Monte Carlo code for modeling diffusion in Ni-Al. The code was designed to interface with a cluster expansion code.

  • Brigham Young University

    Research Assistant

    Developed cluster expansion code for modeling the energetics of alloy systems confined to a lattice. Incorporated Bayesian compressive sensing into the cluster expansion model which resulted in better models constructed in much less time than the previous state-of-the-art. Worked extensively with Monte-Carlo simulations including thermodynamic Monte-Carlo on a fixed lattice, metadynamics for retrieving the free energy function, and wang-landau which retrieves the entropy of an alloy. Also collaborated on an effort to developed a high throughput database of materials properties information from first principles calculations.

  • BYU-Idaho

    Physics tutor

    Conducted one on one tutoring sessions as well as group meetings.

  • BYU-Idaho

    Physics Faculty

    Lance worked at BYU-Idaho as a Physics Faculty

  • Idaho National Laboratory

    Intern

    Worked in the ultrasonics lab developing transducers for scanning the interior of nuclear waste storage containers.

Education

  • Brigham Young University - Idaho

    Bachelor of Science

    Physics

  • Brigham Young University

    Doctor of Philosophy (Ph.D.)

    Computational materials physics

  • Brigham Young University

    Postdoctoral researcher


    Developed a kinetic Monte Carlo code for modeling diffusion in Ni-Al. The code was designed to interface with a cluster expansion code.

  • Brigham Young University

    Research Assistant


    Developed cluster expansion code for modeling the energetics of alloy systems confined to a lattice. Incorporated Bayesian compressive sensing into the cluster expansion model which resulted in better models constructed in much less time than the previous state-of-the-art. Worked extensively with Monte-Carlo simulations including thermodynamic Monte-Carlo on a fixed lattice, metadynamics for retrieving the free energy function, and wang-landau which retrieves the entropy of an alloy. Also collaborated on an effort to developed a high throughput database of materials properties information from first principles calculations.

Publications

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Ground state characterizations of systems predicted to exhibit L1$_1$ or L1$_3$ crystal structures

    Physical Review B

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Ground state characterizations of systems predicted to exhibit L1$_1$ or L1$_3$ crystal structures

    Physical Review B

  • AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations.

    Computational Materials Science

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Ground state characterizations of systems predicted to exhibit L1$_1$ or L1$_3$ crystal structures

    Physical Review B

  • AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations.

    Computational Materials Science

  • Generating derivative superstructures at a fixed concentration

    Computational Materials Science

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Ground state characterizations of systems predicted to exhibit L1$_1$ or L1$_3$ crystal structures

    Physical Review B

  • AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations.

    Computational Materials Science

  • Generating derivative superstructures at a fixed concentration

    Computational Materials Science

  • Cluster Expansion made easy with Bayesian Compressive Sensing

    Physical Review B

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Ground state characterizations of systems predicted to exhibit L1$_1$ or L1$_3$ crystal structures

    Physical Review B

  • AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations.

    Computational Materials Science

  • Generating derivative superstructures at a fixed concentration

    Computational Materials Science

  • Cluster Expansion made easy with Bayesian Compressive Sensing

    Physical Review B

  • Revisiting the CuPt3 prototype and the L13 structure

    Acta Materialia

  • Order phases in ruthenium binary alloys from high-throughput first principles

    Physical Review B

  • Ground state characterizations of systems predicted to exhibit L1$_1$ or L1$_3$ crystal structures

    Physical Review B

  • AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations.

    Computational Materials Science

  • Generating derivative superstructures at a fixed concentration

    Computational Materials Science

  • Cluster Expansion made easy with Bayesian Compressive Sensing

    Physical Review B

  • Revisiting the CuPt3 prototype and the L13 structure

    Acta Materialia

  • Compressive Sensing as a Paradigm for building Physics Models

    Physical Review B

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